
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "1"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 116 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 111 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	88.999962	98.247317	154.730107	175.609790	30.646425	38.728772	93.140927	117.835396	0.0168	0.0160	0.0007	1.163417	1.159667
2459593	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	91.330138	84.103664	182.145926	165.673499	67.937496	54.253836	215.513519	184.723556	0.0166	0.0167	0.0004	1.156043	1.160020
2459592	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	5.596284	19.918511	66.024058	79.104347	91.136903	85.952445	104.417026	98.492233	0.0172	0.0161	0.0010	nan	nan
2459591	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	237.258215	150.939764	284.411723	253.893110	81.683605	89.538962	647.409849	646.961589	0.0160	0.0162	0.0003	1.190165	1.190645
2459590	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	222.551399	132.584148	212.016564	179.813466	47.445327	81.527368	325.765954	266.612888	0.0162	0.0167	0.0004	1.121752	1.128357
2459589	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	302.960705	120.602761	253.033387	181.572367	57.437431	68.028943	353.243370	216.601613	0.0160	0.0163	0.0004	1.135298	1.146171
2459588	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	69.230961	91.898936	216.447238	227.901471	45.285645	44.998818	83.707903	96.585850	0.0164	0.0162	0.0003	1.133077	1.131302
2459587	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	148.289963	89.058468	331.638885	268.366060	79.053787	41.498159	555.897586	358.407625	nan	nan	nan	0.916431	0.918040
2459586	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	145.689710	125.393019	68.072832	65.670718	21.935009	21.870261	487.025366	522.616916	0.0166	0.0161	0.0006	1.244636	1.244725
2459585	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	69.680097	58.943305	48.383839	43.495941	10.551248	9.545598	680.150058	673.346073	0.0166	0.0164	0.0004	0.000000	0.000000
2459584	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	97.501984	141.203302	257.255724	260.032604	20.196621	29.388192	122.232613	169.045666	0.0165	0.0163	0.0004	0.924371	0.926607
2459583	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	54.269978	84.378517	79.128001	73.185563	35.364595	40.228012	222.658910	268.206834	0.0170	0.0169	0.0004	1.063913	1.064781
2459582	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	53.290873	74.489528	73.906267	67.196319	58.509570	43.396827	335.168745	290.841550	0.0163	0.0163	0.0004	1.216416	1.215090
2459581	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	74.558802	91.920768	80.323083	77.280156	26.799232	39.777578	267.703604	330.903535	0.0168	0.0163	0.0006	1.183697	1.180412
2459580	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	99.782114	89.872104	103.837963	84.859029	55.034375	40.454521	492.500929	330.052120	0.0163	0.0162	0.0004	1.213851	1.214062
2459579	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	54.645871	73.228845	97.005554	91.791044	50.356553	52.648022	639.600886	570.070751	0.0164	0.0163	0.0003	1.152842	1.147914
2459578	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	7.617488	10.650283	38.243778	39.053852	185.736461	264.294340	1005.928522	1356.203493	0.0163	0.0162	0.0003	nan	nan
2459577	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	59.302925	92.933246	71.957884	76.181713	51.299484	58.346330	331.544919	452.695315	0.0169	0.0163	0.0004	1.169576	1.165257
2459576	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	43.545256	88.744254	52.010901	64.637993	28.233196	49.610760	287.479002	496.003745	0.0169	0.0161	0.0005	0.000000	0.000000
2459575	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	35.921121	89.667926	59.376515	75.285486	26.447782	52.795053	40.528253	104.079510	0.0165	0.0163	0.0003	0.000000	0.000000
2459574	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	56.220729	66.854402	58.384954	60.916745	39.757419	75.636213	188.858724	331.810309	0.0164	0.0163	0.0004	0.998619	0.997150
2459573	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	58.872595	71.473173	101.711609	100.751667	40.679889	62.710754	450.892196	532.361415	0.0166	0.0163	0.0004	0.000000	0.000000
2459572	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	57.054529	73.976146	56.999651	54.357398	27.565654	39.859450	581.016382	774.395378	0.0163	0.0164	0.0003	0.000000	0.000000
2459571	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	8.207032	9.456296	51.340933	34.796239	308.358488	193.020726	1887.559832	1184.032111	0.0161	0.0164	0.0003	nan	nan
2459570	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	51.648759	105.781830	68.172889	74.594571	14.843121	30.736964	369.004323	682.005348	0.0167	0.0164	0.0004	0.000000	0.000000
2459569	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	165.283506	107.843286	109.680712	79.506509	37.926645	37.070454	65.696169	57.477674	0.0162	0.0162	0.0005	1.000526	1.005623
2459566	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	71.575188	72.289701	84.350103	72.500278	50.217741	42.685715	260.854535	235.547867	0.0165	0.0162	0.0005	1.050761	0.463918
2459565	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	2.744448	2.744448	2.569265	2.569265	0.646598	0.646598	0.135260	0.135260	nan	nan	nan	0.000000	0.000000
2459564	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	73.274769	71.906176	83.883359	73.201445	5.963467	10.957773	196.604823	262.009603	0.0161	0.0164	0.0004	1.159506	1.162749
2459563	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	55.200055	75.237394	149.252668	148.504148	35.438656	46.177974	373.270540	373.258904	0.0165	0.0163	0.0003	0.000000	0.000000
2459562	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	48.693947	94.943177	39.145068	50.860314	11.105158	33.625050	197.696438	476.496119	0.0162	0.0160	0.0003	1.109483	1.105130
2459561	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	63.949335	63.933838	45.014582	39.838177	20.520521	12.881521	646.590626	509.503718	0.0163	0.0161	0.0004	0.758159	0.756420
2459560	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	37.253016	67.842665	36.798473	37.425183	9.377673	13.547413	226.650155	359.298244	0.0164	0.0162	0.0004	0.974876	0.980407
2459559	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	55.072722	66.808014	42.463560	38.991123	5.588942	9.517396	249.199569	296.342962	0.0163	0.0162	0.0004	1.200685	1.202449
2459558	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	104.777168	92.112806	97.924435	82.681021	56.359554	50.092797	754.518116	576.506351	0.0162	0.0162	0.0002	1.234512	1.231503
2459557	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0165	0.0165	0.0004	nan	nan
2459556	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	92.184014	84.503473	102.835845	83.164403	60.073375	40.602513	1522.903498	879.376565	0.0162	0.0164	0.0004	1.219720	1.222128
2459554	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0164	0.0166	0.0004	nan	nan
2459553	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0161	0.0164	0.0004	nan	nan
2459552	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	61.554131	89.069035	112.818495	111.308906	60.979274	72.320883	379.800612	493.025615	0.0164	0.0162	0.0004	0.000000	0.000000
2459551	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	73.395542	59.895998	56.177802	48.750037	35.181320	26.649966	701.709132	525.659965	0.0163	0.0161	0.0004	1.192351	1.196613
2459550	RF_maintenance	-	97.53%	97.53%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0432	0.0433	0.0002	nan	nan
2459549	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	132.993794	86.411435	123.668579	84.500509	77.083679	50.140619	986.153086	525.022350	0.0161	0.0164	0.0003	1.188315	1.191577
2459542	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	106.240213	91.705172	210.887285	168.923442	6.219250	5.899949	482.425900	472.692200	0.0161	0.0163	0.0004	1.168211	1.169474
2459541	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	10.937327	11.201291	46.459684	46.857024	695.489723	673.335539	23.504405	33.878546	0.0169	0.0169	0.0004	1.176835	1.177462
2459540	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	47.782752	78.604874	38.590902	41.902975	21.371903	44.353763	157.270817	281.442923	0.0166	0.0162	0.0004	1.078964	1.075430
2459536	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	242.173754	132.082634	201.694709	131.886195	129.903616	70.056576	1433.180815	707.627931	0.0165	0.0164	0.0004	1.247870	1.252142
2459535	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	44.748603	62.763091	36.509315	39.064514	21.106693	34.180192	223.408635	344.181476	0.0163	0.0162	0.0003	1.210898	1.207633
2459534	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	44.772418	60.772193	36.373762	33.395613	20.429207	36.774711	206.248581	244.864712	0.0162	0.0164	0.0003	1.155516	1.156166
2459533	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	142.211601	99.706685	117.125773	78.458907	88.376258	51.420654	1241.206187	560.247735	0.0159	0.0163	0.0003	1.189393	1.190141
2459532	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	73.881226	99.110807	107.494113	101.134249	52.561688	47.741558	337.718293	408.374898	0.0165	0.0164	0.0003	1.282588	1.272421
2459530	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	46.707224	65.797121	34.901348	36.967972	19.057551	29.747732	297.346875	318.896363	0.0162	0.0163	0.0003	1.199976	1.198275
2459527	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	67.106127	103.951371	126.422856	131.379890	201.909381	235.081983	331.011165	483.816546	0.0162	0.0161	0.0002	0.000000	0.000000
2459523	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	74.555064	115.551406	114.136484	114.589974	58.335295	99.869089	434.507294	635.573550	nan	nan	nan	1.531310	1.535802
2459522	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	64.412592	85.408249	113.730205	108.199815	100.651988	134.103525	483.870608	598.398093	0.0166	0.0165	0.0005	1.313458	1.282946
2459513	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	7.474959	11.597517	30.012049	35.186112	146.726583	285.651032	681.397194	1299.863142	0.0176	0.0164	0.0008	nan	nan
2459508	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	51.172553	104.649010	100.606655	105.218590	50.268485	53.674944	72.541626	105.254078	0.0166	0.0165	0.0003	0.000000	0.000000
2459505	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	57.743509	102.722836	92.539213	100.705954	60.581035	107.476410	348.730595	535.768424	0.0086	0.0069	0.0021	1.160223	1.150074
2459503	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	91.489675	100.238367	191.121330	165.734479	104.913799	56.576595	791.052972	543.068286	0.0058	0.0062	0.0056	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 1 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 1, Node 0:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 1: 2459642

Antenna 1: 2459640

Antenna 1: 2459639

Antenna 1: 2459638

Antenna 1: 2459637

Antenna 1: 2459634

Antenna 1: 2459633

Antenna 1: 2459632

Antenna 1: 2459631

Antenna 1: 2459630

Antenna 1: 2459629

Antenna 1: 2459628

Antenna 1: 2459627

Antenna 1: 2459626

Antenna 1: 2459625

Antenna 1: 2459624

Antenna 1: 2459623

Antenna 1: 2459622

Antenna 1: 2459621

Antenna 1: 2459620

Antenna 1: 2459619

Antenna 1: 2459618

Antenna 1: 2459617

Antenna 1: 2459616

Antenna 1: 2459615

Antenna 1: 2459614

Antenna 1: 2459613

Antenna 1: 2459612

Antenna 1: 2459611

Antenna 1: 2459610

Antenna 1: 2459609

Antenna 1: 2459608

Antenna 1: 2459607

Antenna 1: 2459605

Antenna 1: 2459604

Antenna 1: 2459603

Antenna 1: 2459602

Antenna 1: 2459598

Antenna 1: 2459597

Antenna 1: 2459596

Antenna 1: 2459595

Antenna 1: 2459594

Antenna 1: 2459593

Antenna 1: 2459592

Antenna 1: 2459591

Antenna 1: 2459590

Antenna 1: 2459589

Antenna 1: 2459588

Antenna 1: 2459587

Antenna 1: 2459586

Antenna 1: 2459585

Antenna 1: 2459584

Antenna 1: 2459583

Antenna 1: 2459582

Antenna 1: 2459581

Antenna 1: 2459580

Antenna 1: 2459579

Antenna 1: 2459578

Antenna 1: 2459577

Antenna 1: 2459576

Antenna 1: 2459575

Antenna 1: 2459574

Antenna 1: 2459573

Antenna 1: 2459572

Antenna 1: 2459571

Antenna 1: 2459570

Antenna 1: 2459569

Antenna 1: 2459566

Antenna 1: 2459565

Antenna 1: 2459564

Antenna 1: 2459563

Antenna 1: 2459562

Antenna 1: 2459561

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶